The Role of Springtime Arctic Clouds in Determining Autumn Sea Ice Extent

Abstract

48Recent studies suggest that the atmosphere conditions Arctic sea-ice properties in spring in 49 a way that may be an important factor in predetermining autumn sea ice concentrations. 50Here, the role of clouds in this system is analyzed using surface-based observations from 51Barrow, Alaska. Barrow is a coastal location situated adjacent to the region where 52interannual sea ice variability is largest. Barrow is also along a main transport pathway 53 through which springtime advection of atmospheric energy from lower latitudes to the 54Arctic Ocean occurs. The cloud contribution is quantified using the observed surface 55 radiative fluxes and cloud radiative forcing (CRF) derived therefrom, which can be positive 56 or negative. In low sea ice years enhanced positive CRF (increased cloud cover enhancing 57longwave forcing) in April is followed by decreased negative CRF (decreased cloud cover 58 allowing a relative increase in shortwave forcing) in May and June. The opposite is true in 59 high sea ice years. In either case, the combination and timing of these early and late spring 60 cloud radiative processes can serve to enhance the atmospheric preconditioning of sea ice. 61The net CRF (April and May) measured at Barrow from 1993 through 2014 is negatively 62 correlated with sea ice extent in the following autumn (r 2 = 0.33, p < 0.01). Reanalysis data 63 appears to capture the general timing and sign of the observed CRF anomalies at Barrow 64 and suggests that the anomalies occur over a large region of the central Arctic Ocean, which 65supports the link between radiative processes observed at Barrow and the broader Arctic 66 sea ice extent.

Drivers and Environmental Responses to the Changing Annual Snow Cycle of Northern Alaska

“…This emergence does not appear to be a feature of the trends themselves, however, because the relationship remains unchanged when the analysis is repeated using a linearly detrended time series (dashed lines in the figure). The apparent increase in the importance of advection is consistent with a relative weakening of the influence of cloud forcing, though cloud properties in the far western Arctic and southerly advection have also been linked by several studies (e.g., Kapsch et al 2013;Dong et al 2014;Cox et al 2016), opening questions about how the characteristics of these events may lead to different responses within the Arctic.…”

“…The results here indicate greater influence of warm-air advection during May at BRW since 2000 than previous analysis revealed. Furthermore, advection of warm air is the dominate factor because cloud radiative forcing at Utqiaġvik during May is neutral to positive, becoming larger and negative in June when clouds tend to cool the surface in response to decreasing surface albedo and increasing solar elevation angle (e.g., Dong et al 2010;Cox et al 2016).…”

“…Such events have also been shown to affect the sea ice melt season by studies using both reanalysis data (Kapsch et al 2013) and surface-based observations at Utqiaġvik (Dong et al 2014;Cox et al 2016). The amount of open water in autumn, in turn, is tied to warming of the Arctic's lower atmosphere, a process associated with Arctic amplification (e.g., Serreze et al 2009 and references therein).…”

“…Generally, springtime melting is forced by atmospheric longwave radiative processes, with shortwave processes largely acting as a feedback over both land and sea ice (Persson 2012;Kapsch et al 2013). In addition, cloud anomalies during the spring influence whether shortwave or longwave processes are dominant for a given year (Cox et al 2016;Mortin et al 2016). Recent warming of the permafrost (e.g., Shiklomanov et al 2010) has prompted expectations for increased methane emissions from the tundra, but there is little evidence of this in the 30-yr record at the NOAA GMD observatory near Utqiaġ v i k (hencefor t h BRW) (Sweeney et al 2016), opening questions about the pathways for transfer of carbon between the soil and the atmosphere.…”

A Bird’s-Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska

“…This includes work to understand cloud properties and their radiative impact (e.g., Kay et al 2008;Dong et al 2010, Cox et al 2016, interactions between aerosols and clouds (e.g., Penner et al 2004;Lubin and Vogelmann 2006;Garrett and Zhao 2006), and Arctic aerosol properties (e.g., Quinn et al 2002;Quinn et al 2009;McComiskey and Ferrare 2016). Such studies have resulted in the evaluation of and improvements to numerical models across various scales (e.g., Xie et al 2006;Morrison et al 2009;de Boer et al 2012).…”